Auteurs, date et publication :
Auteurs Yang Liu , Kawssar Haider , Florence Lafouge , Anaïs Feron , Benjamin Loubet , Cristian Focsa , Raluca Ciuraru
Date : 1970
Catégorie(s)
#INRAE #PT-RMSAuteurs, date et publication :
Auteurs Dominique Barloy , Luis Portillo-Lemus , Stacy Krueger-Hadfield , Virginie Huteau , Olivier Coriton
Publication : Peer Community Journal
Date : 2025
Volume : 4
Catégorie(s)
#INRAE #PEARLAuteurs, date et publication :
Auteurs Eglantine Mathieu‐Bégné , Simon Blanchet , Olivier Rey , Eve Toulza , Charlotte Veyssière , Sophie Manzi , Maxim Lefort , Orlane Scelsi , Géraldine Loot
Publication : Molecular Ecology
Date : 2023
Pages : mec.16901
Catégorie(s)
#INRAE #PEARLRésumé
Predicting Gross Primary Productivity (GPP) across diverse ecosystems is essential for understanding the global carbon cycle and managing environmental resources effectively. This study evaluates the effectiveness of three different models, namely SARIMAX, XGBoost, and LSTM in estimating GPP using a combination of in-situ measurements and remote sensing data across various European ecosystems. The research consist of two main stages: the development of site-specific models to understand individual site characteristics and the creation of a unified model capable of generalizing predictions across different ecosystems without further site-specific adjustments. Our findings indicate that XGBoost consistently outperformed other models, showing superior prediction accuracy and robustness, particularly when generalized across multiple sites. SARIMAX and LSTM models also demonstrated useful capabilities, though with some limitations in specific contexts such as catastrophic forgetting in LSTM and poor performance in peak GPP predictions by SARIMAX. The inclusion of specific remote sensing indices, like the modified normalized difference vegetation index (MNDVI) and the enhanced vegetation index (EVI), significantly improved model performance across varied ecosystems. This study underscores the potential of integrating machine learning techniques with traditional ecological modeling approaches to enhance the prediction of GPP, which can significantly contribute to ecological management and climate change mitigation strategies. Future work should focus on refining these models’ ability to handle diverse data sets and improve their predictive reliability across global ecosystems.
Auteurs, date et publication :
Auteurs K. Karisma
Date : 2024
Catégorie(s)
#ACBB #ACBB Mons #INRAERésumé
Purpose For the agroecological transition, the rhizosphere is a critical interface for plants to acquire resources and to enhance plant health with limited inputs. In the present study, we developed a new indicator to estimate and monitor the intensity of plantsoil-microbiota interactions under field conditions.
Auteurs, date et publication :
Auteurs Sébastian Mira , Mathieu Emily , Christophe Mougel , Morgane Ourry , Edith Le Cadre
Publication : Plant and Soil
Date : 2025
Volume : 478
Issue : 1-2
Pages : 325-346
Catégorie(s)
#BiochemEnv #INRAERésumé
Abstract. Empirical evidence demonstrates that lakes and reservoirs are warming across
the globe. Consequently, there is an increased need to project future
changes in lake thermal structure and resulting changes in lake
biogeochemistry in order to plan for the likely impacts. Previous studies of
the impacts of climate change on lakes have often relied on a single model
forced with limited scenario-driven projections of future climate for a
relatively small number of lakes. As a result, our understanding of the
effects of climate change on lakes is fragmentary, based on scattered
studies using different data sources and modelling protocols, and mainly
focused on individual lakes or lake regions. This has precluded
identification of the main impacts of climate change on lakes at global and
regional scales and has likely contributed to the lack of lake water quality
considerations in policy-relevant documents, such as the Assessment Reports
of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a
simulation protocol developed by the Lake Sector of the Inter-Sectoral
Impact Model Intercomparison Project (ISIMIP) for simulating climate change
impacts on lakes using an ensemble of lake models and climate change
scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake
simulations driven by climate forcing from gridded observations and
different Earth system models under various representative greenhouse gas
concentration pathways (RCPs), all consistently bias-corrected on a
0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lake
models were forced with these data to project the thermal structure of 62
well-studied lakes where data were available for calibration under
historical conditions, and using uncalibrated models for 17 500 lakes
defined for all global grid cells containing lakes. In ISIMIP phase 3, this
approach was expanded to consider more lakes, more models, and more
processes. The ISIMIP Lake Sector is the largest international effort to
project future water temperature, thermal structure, and ice phenology of
lakes at local and global scales and paves the way for future simulations of
the impacts of climate change on water quality and biogeochemistry in lakes.
Auteurs, date et publication :
Auteurs Malgorzata Golub , Wim Thiery , Rafael Marcé , Don Pierson , Inne Vanderkelen , Daniel Mercado-Bettin , R. Iestyn Woolway , Luke Grant , Eleanor Jennings , Benjamin M. Kraemer , Jacob Schewe , Fang Zhao , Katja Frieler , Matthias Mengel , Vasiliy Y. Bogomolov , Damien Bouffard , Marianne Côté , Raoul-Marie Couture , Andrey V. Debolskiy , Bram Droppers
Publication : Geoscientific Model Development
Date : 2022
Volume : 15
Issue : 11
Pages : 4597-4623
Catégorie(s)
#INRAE #OLARésumé
Severe deterioration of water quality in lakes, characterized by overabundance of algae and declining dissolved oxygen in the deep lake (DOB), was one of the ecological crises of the 20th century. Even with large reductions in phosphorus loading, termed “reoligotrophication,” DOB and chlorophyll (CHL) have often not returned to their expected pre–20th-century levels. Concurrently, management of lake health has been confounded by possible consequences of climate change, particularly since the effects of climate are not neatly separable from the effects of eutrophication. Here, using Lake Geneva as an iconic example, we demonstrate a complementary alternative to parametric models for understanding and managing lake systems. This involves establishing an empirically-driven baseline that uses supervised machine learning to capture the changing interdependencies among biogeochemical variables and then combining the empirical model with a more conventional equation-based model of lake physics to predict DOB over decadal time-scales. The hybrid model not only leads to substantially better forecasts, but also to a more actionable description of the emergent rates and processes (biogeochemical, ecological, etc.) that drive water quality. Notably, the hybrid model suggests that the impact of a moderate 3°C air temperature increase on water quality would be on the same order as the eutrophication of the previous century. The study provides a template and a practical path forward to cope with shifts in ecology to manage environmental systems for non-analogue futures.
Auteurs, date et publication :
Auteurs Ethan R. Deyle , Damien Bouffard , Victor Frossard , Robert Schwefel , John Melack , George Sugihara
Publication : Proceedings of the National Academy of Sciences
Date : 2022
Volume : 119
Issue : 26
Pages : e2102466119
Catégorie(s)
#INRAE #OLARésumé
Water pollution is a significant threat to aquatic ecosystems. Various methods of monitoring, such as in situ approaches, are currently available to assess its impact. In this paper we examine the use of fish in active biomonitoring to study contamination and toxicity of surface waters. We analysed 148 previous studies conducted between 2005 and 2022, including both marine and freshwater environments, focusing on the characteristics of the organisms used as well as the principal goals of these studies. The main conclusions we drew are that a wide range of protocols and organisms have been used but there is no standardised method for assessing the quality of aquatic ecosystems on a more global scale. Additionally, the most commonly used developmental stages have been juveniles and adults. At these stages, the most frequently used species were the fathead minnow (Pimephales promelas) and two salmonids: rainbow trout (Oncorhynchus mykiss) and brown trout (Salmo trutta). Few studies used earlier stages of development (embryos or larvae), mostly due to the difficulty of obtaining fish embryos and caging them in the field. Finally, we identified research gaps in active biomonitoring for water quality assessment which could indicate useful directions for future research and development.
Auteurs, date et publication :
Auteurs Sarah Bancel , Jérôme Cachot , Corentin Bon , Éric Rochard , Olivier Geffard
Publication : Environmental Pollution
Date : 2025
Volume : 360
Pages : 124661
Catégorie(s)
#INRAE #XPOAuteurs, date et publication :
Auteurs Sami Jaballah , Guglielmo Fernandez Garcia , François Martignac , Nicolas Parisey , Stéphane Jumel , Jean-Marc Roussel , Olivier Dézerald
Publication : Aquatic Ecology
Date : 2023
Catégorie(s)
#INRAE #PEARLRésumé
Soil organic carbon is one of the largest surface pools of carbon that humans can manage in order to partially mitigate annual anthropogenic CO2 emissions. A significant element to assess soil sequestration potential is the carbon age, which is evaluated by modelling or experimentally using carbon isotopes. Results, however, are not consistent. The 14C derived approach seems to overestimate by a factor of 6–10 the average carbon age in soils estimated by modeling and 13C approaches and thus the sequestration potential. A fully independent method is needed. The cosmogenic chlorine nuclide, 36Cl, is a potential alternative. 36Cl is a naturally occurring cosmogenic radionuclide with a production that increased by three orders of magnitude during nuclear bomb tests. Part of this production is retained by soil organic matter in organochloride form and hence acts as a tracer of the fate of soil organic carbon. We here quantify the fraction and the duration of 36Cl retained in the soil and we show that retention time increases with depth from 20 to 322 years, in agreement with both modelling and 13C-derived estimates. This work demonstrates that 36Cl retention duration can be a proxy for the age of soil organic carbon.
Auteurs, date et publication :
Auteurs Cécile Grapeloup , Sophie Cornu , Xavier Giraud , Julie Pupier , Aster Team , Valery Guillou , Philippe Ciffroy , Beatriz Lourino Cabana , Cécile Couegnas , Christine Hatté , Lucilla Benedetti
Publication : Scientific Reports
Date : 2023
Volume : 13
Issue : 1
Pages : 15085